The use of predictive and prognostic biomarkers paired with targeted cancer therapies may hold the key to reducing drug development time, improving drug efficacy, and guiding clinical decision making. While there have been advances in cancer treatment, chemotherapy remains largely inefficient and ineffective. One reason for the generally poor performance of chemotherapy is that the selected treatment is often not closely matched to the individual patient's disease. A personalized medicine approach that couples precise diagnostics with therapeutics might alleviate this problem.
Further complicating widespread application of chemotherapies is that subsets of patients are likely to incur life-threatening treatment-related toxicities. For example, tumor lysis syndrome (TLS) may cause a patient to be unable to receive a treatment for its cancer. Again, personalized medicine approaches seek to improve clinical outcomes by identifying patients likely to exhibit such toxicities and eliminate them from consideration for treatments likely to exhibit said toxicity.
Diagnostic approaches are needed that can predict drug toxicity, including susceptibility to TLS, and drug efficacy in a patient.